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This computed tomography system is intended to generate and process cross-sectional images of patients by computer reconstruction of x-ray transmission data.

The images delivered by the system can be used by a trained staff as an aid in diagnosis, treatment and radiation therapy planning as well as for diagnostic and therapeutic interventions.

This CT system can be used for low dose lung cancer screening in high risk populations*.

*As defined by professional medical societies. Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

Siemens intends to update the software version syngo CT VB20 (update) for the following NAEOTOM Alpha class CT systems:

Dual Source NAEOTOM CT scanner systems:

• NAEOTOM Alpha (trade name ex-factory CT systems: NAEOTOM Alpha.Peak; trade name installed base CT systems with SW upgrade only: NAEOTOM Alpha)

For simplicity, the product name of NAEOTOM Alpha will be used throughout this submission instead of the trade name NAEOTOM Alpha.Peak.

• NAEOTOM Alpha.Pro

Single Source NAEOTOM CT scanner system:

• NAEOTOM Alpha.Prime

The subject devices NAEOTOM Alpha (trade name ex-factory CT systems: NAEOTOM Alpha.Peak) and NAEOTOM Alpha.Pro with software version SOMARIS/10 syngo CT VB20 (update) are Computed Tomography X-ray systems which feature two continuously rotating tube-detector systems, denominated as A- and B-systems respectively (dual source NAEOTOM CT scanner system).

The subject device NAEOTOM Alpha.Prime with software version SOMARIS/10 syngo CT VB20 (update) is a Computed Tomography X-ray system which features one continuously rotating tube-detector systems, denominated as A-system (single source NAEOTOM CT scanner system).

The detectors' function is based on photon-counting technology.

In this submission, the above-mentioned CT scanner systems are jointly referred to as subject devices by "NAEOTOM Alpha class CT scanner systems".

The NAEOTOM Alpha class CT scanner systems with SOMARIS/10 syngo CT VB20 (update) produce CT images in DICOM format, which can be used by trained staff for post-processing applications commercially distributed by Siemens and other vendors. The CT images can be used by a trained staff as an aid in diagnosis, treatment and radiation therapy planning as well as for diagnostic and therapeutic interventions. The radiation therapy planning support includes, but is not limited to, Brachytherapy, Particle Therapy including Proton Therapy, External Beam Radiation Therapy, Surgery. The computer system delivered with the CT scanner is able to run optional post-processing applications.

Only trained and qualified users, certified in accordance with country-specific regulations, are authorized to operate the system. For example, physicians, radiologists, or technologists. The user must have the necessary U.S. qualifications in order to diagnose or treat the patient with the use of the images delivered by the system.

The platform software for the NAEOTOM Alpha class CT scanner systems is syngo CT VB20 (update) (SOMARIS/10 syngo CT VB20 (update)). It is a command-based program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation. The software platform provides plugin software interfaces that allow for the use of specific commercially available post-processing software algorithms in an unmodified form from the cleared stand-alone post-processing version.

Software version syngo CT VB20 (update) (SOMARIS/10 syngo CT VB20 (update)) shall support additional software features compared to the software version of the predicate devices NAEOTOM Alpha class CT systems with syngo CT VB20 (SOMARIS/10 syngo CT VB20) cleared in K243523.

Software version SOMARIS/10 syngo CT VB20 (update) will be offered ex-factory and as optional upgrade for the existing NAEOTOM Alpha class systems.

The bundle approach is feasible for this submission since the subject devices have similar technological characteristics, software operating platform, and supported software characteristics. All subject devices will support previously cleared software and hardware features in addition to the applicable modifications as described within this submission. The intended use remains unchanged compared to the predicate devices.

The provided document describes the acceptance criteria and a study that proves the device meets those criteria for the NAEOTOM Alpha CT Scanner Systems. However, the document primarily focuses on demonstrating substantial equivalence to a predicate device and safety and effectiveness based on non-clinical testing and adherence to standards, rather than detailing a specific clinical performance study with defined acceptance criteria for a diagnostic aid.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a specific table of acceptance criteria with corresponding performance metrics in the way one would typically find for a diagnostic AI device (e.g., sensitivity, specificity, AUC). Instead, it states that:

• Acceptance Criteria for Software: "The test specification and acceptance criteria are related to the corresponding requirements." and "The test results show that all of the software specifications have met the acceptance criteria."
• Acceptance Criteria for Features: "Test results show that the subject devices...is comparable to the predicate devices in terms of technological characteristics and safety and effectiveness and therefore are substantially equivalent to the predicate devices."
• Performance Claim: "The conclusions drawn from the non-clinical and clinical tests demonstrate that the subject devices are as safe, as effective, and perform as well as or better than the predicate devices."

The closest the document comes to defining and reporting on "performance criteria" for a specific feature, beyond basic safety and technical functionality, are for the HD FoV 5.0 and ZeeFree RT algorithms.

2. Sample Size Used for the Test Set and Data Provenance

The document mentions "physical and anthropomorphic phantoms" for HD FoV 5.0 and "homogeneous water phantom" and "phantom with tissue-equivalent inserts," and "dynamic thorax phantom" for ZeeFree RT. It also refers to "retrospective blinded rater studies of respiratory 4D CT examinations performed at two institutions" for ZeeFree RT, but does not specify the sample size (number of cases/patients) or the country of origin for these real-world examination datasets. The data provenance (retrospective/prospective) is stated for the rater study for ZeeFree RT as retrospective, but not for the HD FoV 5.0 rater study (though implied by "retrospective blinded rater study").

3. Number of Experts and Qualifications for Ground Truth

For the HD FoV 5.0 and ZeeFree RT rater studies, the experts were "board-approved radio-oncologists and medical physicists." The number of experts is not specified, nor is their specific years of experience.

4. Adjudication Method for the Test Set

The document explicitly states "retrospective blinded rater study" for HD FoV 5.0 and ZeeFree RT. However, it does not specify the adjudication method (e.g., 2+1, 3+1, none) if there were multiple raters and disagreements.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

The document states that for HD FoV 5.0 and ZeeFree RT, "the performance of the algorithm was evaluated by board-approved radio-oncologists and medical physicists by means of retrospective blinded rater study." This indicates a reader study, which is often a component of an MRMC study.

However, the study described does not appear to be comparing human readers with AI assistance vs. without AI assistance. Instead, for HD FoV 5.0, it's comparing the new algorithm's results to its predecessor, HD FoV 4.0. For ZeeFree RT, it's comparing the reconstruction to "Standard reconstruction" and assessing if it introduces errors or new artifacts. It's an evaluation of the algorithm's output, not necessarily a direct measure of human reader improvement with AI assistance. Therefore, no effect size for human reader improvement with AI vs. without AI assistance is reported because this specific type of comparative effectiveness study was not described.

6. Standalone (Algorithm Only) Performance Study

Yes, standalone (algorithm only) performance was conducted. The bench testing described for both HD FoV 5.0 and ZeeFree RT involves detailed evaluations of the algorithms' outputs using phantoms and comparing them to established standards or previous versions. For example, for ZeeFree RT, the bench test objectives include demonstrating that it "introduces no relevant errors in terms of CT values and noise levels measured in a homogeneous water phantom" and "does not introduce relevant new artefacts." This is an assessment of the algorithm's direct output.

7. Type of Ground Truth Used

The ground truth used primarily appears to be:

• Phantom-based measurements: For HD FoV 5.0 (physical and anthropomorphic phantoms) and ZeeFree RT (homogeneous water phantom, tissue-equivalent inserts, static torso phantom, dynamic thorax phantom). These phantoms have known properties which serve as ground truth for evaluating image quality metrics.
• Expert Consensus/Interpretation: For HD FoV 5.0 and ZeeFree RT, it involved "board-approved radio-oncologists and medical physicists" in "retrospective blinded rater studies." This suggests the experts' interpretations (potentially comparing image features or diagnostic quality) formed a part of the ground truth or served as the primary evaluation method. The text doesn't specify if there was a pre-established "true" diagnosis or condition for these clinical cases, or if the experts were rating image quality or agreement with a reference standard.

8. Sample Size for the Training Set

The document does not specify the sample size for the training set for any of the algorithms or software features. This document is a 510(k) summary, which generally focuses on justification for substantial equivalence rather than detailed algorithm development specifics.

9. How the Ground Truth for the Training Set Was Established

The document does not describe how the ground truth for the training set was established, as it does not provide information about the training set itself.

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